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. 2022 Jun 30;11(2):417-426.
doi: 10.1556/2006.2022.00044. Print 2022 Jul 13.

Brain structural covariation linked to screen media activity and externalizing behaviors in children

Yihong Zhao  1   2   3 , Martin Paulus  4   5 , Kara S Bagot  6 , R Todd Constable  7 , H Klar Yaggi  8   9 , Nancy S Redeker  10 , Marc N Potenza  11   12   13   14
Affiliations

Brain structural covariation linked to screen media activity and externalizing behaviors in children

Yihong Zhao et al. J Behav Addict. .

Abstract

Background and aims: Screen media activity (SMA) may impact neurodevelopment in youth. Cross-sectionally, SMA has been linked to brain structural patterns including cortical thinning in children. However, it remains unclear whether specific brain structural co-variation patterns are related to SMA and other clinically relevant measures such as psychopathology, cognition and sleep in children.

Methods: Adolescent Brain Cognitive Development (ABCD) participants with useable baseline structural imaging (N = 10,691; 5,107 girls) were analyzed. We first used the Joint and Individual Variation Explained (JIVE) approach to identify cortical and subcortical covariation pattern(s) among a set of 221 brain features (i.e., surface area, thickness, or cortical and subcortical gray matter (GM) volumes). Then, the identified structural covariation pattern was used as a predictor in linear mixed-effect models to investigate its associations with SMA, psychopathology, and cognitive and sleep measures.

Results: A thalamus-prefrontal cortex (PFC)-brainstem structural co-variation pattern (circuit) was identified. The pattern suggests brainstem and bilateral thalamus proper GM volumes covary more strongly with GM volume and/or surface area in bilateral superior frontal gyral, rostral middle frontal, inferior parietal, and inferior temporal regions. This covariation pattern highly resembled one previously linked to alcohol use initiation prior to adulthood and was consistent in girls and boys. Subsequent regression analyses showed that this co-variation pattern associated with SMA (β = 0.107, P = 0.002) and externalizing psychopathology (β = 0.117, P = 0.002), respectively.

Discussion and conclusions: Findings linking SMA-related structural covariation to externalizing psychopathology in youth resonate with prior studies of alcohol-use initiation and suggest a potential neurodevelopmental mechanism underlying addiction vulnerability.

Keywords: addictive behaviors; child; cortical thinning; externalizing behavior; screen media activity.

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Conflict of interest statement

The authors declare no conflicts of interest. Dr. Potenza has consulted for Opiant Therapeutics, Game Day Data, Baria-Tek, the Addiction Policy Forum, AXA and Idorsia Pharmaceuticals; has been involved in a patent application with Yale University and Novartis; has received research support from Mohegan Sun Casino and the National Center for Responsible Gaming; has participated in surveys, mailings or telephone consultations related to drug addiction, impulse-control disorders or other health topics; has consulted for and/or advised gambling and legal entities on issues related to impulse-control/addictive disorders; has provided clinical care in a problem gambling services program; has performed grant reviews for research-funding agencies; has edited journals and journal sections; has given academic lectures in grand rounds, CME events and other clinical or scientific venues; and has generated books or book chapters for publishers of mental health texts. Dr. Potenza is an associate editor of the Journal of Behavioral Addictions. The other authors do not report disclosures.

Figures

Fig. 1.
Fig. 1.
Plots are shown of brain regions in the joint component with loadings larger than 0.13 (approximately corresponding to the top 5% of regions with the largest loading magnitudes). Interior and exterior views of the brain regions are presented for each morphological measure. This JIVE component was related to both total screen time (β = 0.107, P = 0.002) and externalizing behaviors (β = 0.117, P = 0.002).
Fig. 2.
Fig. 2.
Overlayed scatter plot of the loadings for 221 ROI (region of interest) structural features in the joint components derived from the ABCD (Adolescent Brain Cognitive Development) baseline data and the HCP (Human Connectome Project) subsample.
See this image and copyright information in PMC

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